Image processing system and spatial noise reducing method

Abstract

The invention discloses an image processing system and method thereof. The image processing system includes an local variance estimator, a noise detector, a spatial de-noise filter. The local variance estimator estimates each pixel of an input image signal to separately output a local variance value of each pixel, and generates a noise threshold according to the local variance values. The noise detector determines which pixel indicates noise or image according to the noise threshold. The spatial de-noise filter filers the pixel indicating noise to generate an output image signal.

Description

BACKGROUND OF THE INVENTION[0001](a) Field of the Invention[0002]The invention relates to an image processing system and the method thereof, particularly to an image processing system and the method thereof for eliminating noises and remaining image details on an image.[0003](b) Description of the Related Art[0004]FIG. 1 shows a schematic diagram illustrating an prior image processing system. Generally, an image processing system 10 includes a low-pass filter for removing noises on an image. The low-pass filter filters out the high-frequency noises from the input image signal Vi but remains the low-frequency portion of the input image signal Vi to generate an output image signal Vo, thereby producing the function of removing noises on an image.[0005]However, in the case of eliminating spatial noises on an image, signal processing method according to prior art, such as using a prior low-pass filter for filtering, not only eliminates noises but also makes the image blurred. The prior ...

AI Technical Summary

Benefits of technology

[0006]In light of the above-mentioned problem, one object of the invention is to provide an image processing system and an spatial noise reducing method that can not only eliminate spatial image noises but also remain image details.

[0011]The technique of embodiments calculates the local variance values of each pixel and its adjacent pixels of an input image signal to acquire the degree of variance between pixels in the whole image and then uses the degree of variance to determine that each pixel is either noises or image details (such as an image border / boundary) on an image. Then, the weight of each pixel is adjusted correspondingly to eliminate noises and enhance the border or boundary on an image so that the problem in the prior art can be solved, and the effect of eliminating noises and remaining image details at the same time can be achieved.

Problems solved by technology

However, in the case of eliminating spatial noises on an image, signal processing method according to prior art, such as using a prior low-pass filter for filtering, not only eliminates noises but also makes the image blurred.

The prior signal processing method cannot achieve the effect of eliminating noises and remaining image details at the same time.

Thus, the image quality becomes worse.

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